基于四元数非局部低秩和全变分的图像混合噪声去噪算法  

Image Mixed Denoising Using Quaternion-Based Non-Local Low Rank and Total Variation

作　　者：李潇瑶 王炼红[1] 周怡聪 章兢[1] LI Xiao-yao;WANG Lian-hong;ZHOU Yi-cong;ZHANG Jing(College of Electrical and Information Engineering,Hunan University,Changsha,Hunan 410082,China;Department of Computer and Information Science,University of Macao,Macao 999078,China)

机构地区：[1]湖南大学电气与信息工程学院,湖南长沙410082 [2]澳门大学电脑与资讯科学系,中国澳门999078

出　　处：《电子学报》2023年第4期975-983,共9页Acta Electronica Sinica

基　　金：国家重点研发计划(No.2019YFE0105300);国家自然科学基金(No.61573299);中国高校产学研创新基金重点项目(No.2019ITA01016)。

摘　　要：许多彩色图像去噪算法没有充分利用图像块间和颜色分量间的相关性,在去噪时丢失大量细节,容易导致颜色失真,从而影响后续处理.此外,真实的图像噪声通常是高斯-脉冲混合噪声而不是单一类型的,导致许多成熟的仅针对加性高斯噪声或脉冲噪声的去噪算法无法直接使用于真实场景.为解决这些问题,本文提出了基于四元数非局部低秩和全变分的图像混合噪声去除算法.该算法首先将彩色图像从空间域转换至四元数域,然后计算图像的非局部结构相似性和局部梯度,利用四元数域下的L1范数最小化模型,最终实现图像去噪.与现有的彩色图像去噪算法相比,该算法能更有效地保留图像块间、块内以及颜色分量间的相关性.去噪实验结果表明,本文算法在峰值信噪比和结构相似性上分别提高0.21~3.04 dB和1.51%~14.51%,并能在有效去噪和抑制伪影的同时,更好地保持图像细节和颜色信息,对噪声类型和强度变化更具鲁棒性.Many color image denoising methods fail to fully consider the correlations among color channels and lose many details.These always cause color distortion in the denoising results and even affect subsequent image processing tasks.In addition,the realistic noise often consists of different types of noise,such as the mixed Gaussian-impulsive noise,instead of single type.This leads to the failure of direct application in real-world image denoising for some existing denois-ing methods aiming at only additional Gaussian noise or only impulsive noise.To solve these problems,this paper proposes a mixed noise removal method named quaternion-based non-local low rank and total variation.The proposed method first converts the color image from spatial domain to quaternion domain,captures the non-local similarity and local gradient in-formation and then applies the quaternion-based L1-regularized minimization model to denoise color images.Compared with many existing color denoising methods,the proposed method can keep the within-patch,cross-patch and cross-channel correlations of color images.Compared with other competing methods,the proposed method improves the peak signal-to-noise ratio and structure similarity by 0.21~3.04 dB and 1.51%~14.51%,respectively.The visual results demonstrate the su-periority of the proposed method in preserving image details and color information while removing noise and reducing arti-facts.Furthermore,the proposed method is robust to noise type and noise level.

关 键 词：图像去噪 混合噪声 四元数 非局部相似性 低秩 全变分 

分 类 号：TN911.73[电子电信—通信与信息系统]